RNase H2, mutated in Aicardi‐Goutières syndrome, resolves co-transcriptional R-loops to prevent DNA breaks and inflammation

RNase H2 is a specialized enzyme that degrades RNA in RNA/DNA hybrids and deficiency of this enzyme causes a severe neuroinflammatory disease, Aicardi Goutières syndrome (AGS). However, the molecular mechanism underlying AGS is still unclear. Here, we show that RNase H2 is associated with a subset of genes, in a transcription-dependent manner where it interacts with RNA Polymerase II. RNase H2 depletion impairs transcription leading to accumulation of R-loops, structures that comprise RNA/DNA hybrids and a displaced DNA strand, mainly associated with short and intronless genes. Importantly, accumulated R-loops are processed by XPG and XPF endonucleases which leads to DNA damage and activation of the immune response, features associated with AGS. Consequently, we uncover a key role for RNase H2 in the transcription of human genes by maintaining R-loop homeostasis. Our results provide insight into the mechanistic contribution of R-loops to AGS pathogenesis.

RNase H2, the subject of these studies, has two different functions. The most studied, at least in mammals, is the ribonucleotide excision repair (RER) activity, which initiates the removal of ribonucleotides incorporated in DNA during replication. This manuscript addresses the least known function of RNase H2 in processing the RNA strand of R-loops, which are structures formed after transcription when the RNA hybridizes back with the template strand. This work describes the association of RNase H2 to actively transcribed genes, analyzing RNase H2 binding to chromatin and its genomic distribution. An association to chromatin could be due to its RER activity, but they found the interaction to be independent of DNA replication by inhibiting DNA Pol and by using quiescent fibroblasts. They found that RNase H2 and RNA Pol II co-IP in the absence of nucleic acids, suggesting that they are part of the same complex. When RNase H2 is depleted, nascent transcripts are reduced for some gene categories but not (or very minimally) for intron-containing genes, which make the largest portion of RNA Pol II transcripts. Consistent with RNase H2 interacting and processing the R-loops of only a small subset of active genes, DRIP-seq showed more decreased/loss (35,604) than increased/gained (16,647) DRIP peaks in RNase H2 depleted cells, although selecting for genes that are strongly enriched for R-loops, there is an increase in R-loop signal upon RNase H2A depletion in most gene categories except in intron-containing genes. Finally, they try to establish a connection between Rloop accumulation in the absence of RNase H2 and DNA damage and the immune response found in AGS patients.
The main findings of the manuscript are: • RNase H2 interacts with RNA Pol II and acts co-transcriptionally removing R-loops presumably as they are formed to allow proper gene expression. • There is a specific subset of genes that RNase H2 binds, leading to R-loop processing. This group of RNase H2-interacting genes are mostly short genes including histone, snRNA and intronless genes. • They propose a mechanism for R-loop induced DNA damage and immune-response in RNase H2 defective and AGS mutants that requires structure-specific endonucleases cleaving the ssDNA portion of the R-loops. All these results are novel and would be of interest to the fields of RNase H studies, DNA damage and autoinflammatory disorders. Also, they would advance our understanding of how R-loop accumulation affects gene regulation. The data are well presented, and the statistical analyses are appropriate. However, before been accepted for publication a few issues should be addressed: 1. RNASEH2C mRNA is only depleted to about 60% by siRNASEH2C (Extended data figure 1C) and subsequently the protein level of RNase H2C is only reduced to about 50% (Figure 1b) of wt levels forming RNase H2 complexes that are about 50% the amount in wt cells. These small decreases would presumably affect all subsequent data obtained using siRNASEH2C. I would suggest using siRNASH2B instead, which appears to be more effective.  Figure 1a, the fraction of chromatin bound RNase H2 subunits appears to be very similar after siLuc as after depletion of the different components of the RNase H2 complex. It seems that the depletion affects mostly the free form of RNase H2 but shows little effect on the chromatin-bound form, or that the fraction of bound form is very small. 3. Because RNase H2 would be expected to associate with chromatin as part of its RER function, it is important to show convincingly that the association of RNase H2 and RNA Pol II is strong in quiescent fibroblasts, which the data presented in Extended Data Figure 3b does not appear to support well. The inclusion of clear western blot data is needed to help substantiate this association. 4. In figure 4b it is shown that RNase H2 peak coincides with the DRIP peak in cells with wt RNase H2, suggesting that RNase H2 binds but doesn't cleave R-loops enriched regions. Could an explanation for this be proposed? Perhaps RNase H2 binds all or most R-loops but only processes a small portion of them. 5. That the depletion of RNase H2 induces immune-related mRNAs is something that has been described in several systems, and it was previously shown to be associated with its RER activity. To demonstrate an involvement of the R-loop processing activity of RNase H2, the authors used overexpression of RNase H1. They showed that increased RNase H1 activity decreased the expression of immune-related genes. However, overexpression of RNase H1 may have additional effects, such as decreasing mtDNA replication. In addition, it has not been established whether RNase H1 can functionally replace RNase H2 in processing R-loops in mammalian cells. A much better experiment would be to delete the RNASEH2A gene and express the RNaseH2A-RED mutant, which has been successfully used for separating the two activities of RNase H2 and is specific for the removal of R-loops. 6. Does the RNase H1 overexpression system express only the nuclear form of the enzyme, or does it also express the mitochondrial form? This construct should be clearly described.
Reviewer #2 (Remarks to the Author): This manuscript describes the genome-wide profile of RNaseH2 binding to the human genome. The main findings are that RNaseH2 associated with transcribed regions of the genome in a transcriptiondependent manner and through physical association with RNA polymerase II. Loss of RNaseH2 function leads to defects in transcription that appear selective to specific types of transcripts, namely short intronless transcripts. As expected, loss of RNaseH2 leads to increases in R-loops at some loci. These Rloops can lead to DNA damage caused by the XPF/XPG nucleases and activate transcription of inflammatory response genes, which is relevant to the RNaseH2-deficiency disorder Aicardi-Goutieres syndrome. Overall, the manuscript is clear and straightforward and presents a novel finding that RNaseH2 regulates transcription through association with RNA polymerase II and transcribed genes.
I have a number of technical questions, and suggestions for additional analyses that could improve the work. In short, while Figures 1-3 are novel, Figures 4 and 5 primarily serve to validate the literature but do not add much new insight. In the end this leads to a model which lacks some key insights; specifically how and when does RNaseH2 interact with RNA polymerases? how does rapid degradation of a cotranscriptional R-loop promote efficient transcription, and what does this have to do with short genes? How do these R-loops trigger an inflammatory response?
A deeper exploration of some of these questions, even using the authors existing data and some assays they already have working would dramatically strengthen the manuscript.
Major issues: 1. The EU staining data seems to also show that nucleolar intensity is decreased. The authors should test whether RNaseH2 also affects RNA Polymerase I and III transcription, and whether RNA polymerase I and III can be observed in pulldowns of RNaseH2 (as in Fig. 3A). This is a missed opportunity to learn more about how RNaseH2 is actually recruited. For example, if all three polymerases could recruit RNaseH2 then it would suggest that a shared subunit may be responsible for the interaction.
2. The correlation between R-loop levels and RNaseH2 occupancy is quite strange. Naively one would expect higher RNaseH2 at a locus to reduce the lifetime and amount of R-loops present. The authors suggest other factors may compensate. I wonder if catalytic mutants of RNaseH2A would behave the same way in terms of their effects on transcription. The authors could attempt to rescue their siRNA cells with WT or mutant RNaseH2A to determine if the R-loop resolution function is required for the observed effects on global transcription.
3. The induction of immune related genes by qPCR Figure 5f seem to normalize both the siLuc and siXPG to 1 for the mRNA levels. I think the siXPG should not be normalized and should be compared directly to siLuc. Does XPG or XPF knockdown alone increase inflammatory gene expression? It may be that the relative increase in siRNAseH2A is lower, but if the background in siXPG is much higher it could change the interpretation. The way the data is presented does not allow for this kind of comparison. Figure 5e, Might the authors have expected that XPF depletion on its own would have caused DNA damage. The box plot should perhaps show the individual data points, it seems like the siXPF sample has a long tail of cells with damage. Is the distribution normal? Can the authors do a statistical test of siXPF versus control to see if there is an increase in comet tail moment? Currently the siXPF bar (purple) is not compared to the control siRNA bar (white) as far as I can see. This should be done and discussed. Which post-hoc statistical test was used should be indicated in the legend also. In addition, if the damage is really due to R-loops RNaseH1 expression could be included as an additional control, especially since XPF/XPG knockdown do not completely suppress the damage. 5. Is it possible that the immune genes are directly affected by RNaseH2A knockdown due to the transcriptional role? To address any effects the authors could analyze the DRIP, RNAPolII and RNaseH2A occupancy at all of the reporter genes (TNF, STING etc). This is important to rule out direct effects on transcription as opposed to DNA damage-cytoplasmic DNA induced activation. Similarly, the authors rely on mRNA expression but looking at protein level induction and possibly at micronuclei as a cause of STING activation would fill out the story. Additional data to help us understand how these R-loops trigger an inflammatory response would help better justify the focus on AGS in the title.

In
6. The bias toward short genes is not really explained because RNaseH2 and DRIP signal still occupy a lot of normal genes. If it is only when RNaseH2 is depleted that the effect on short genes is seen, then why does it RNaseH2 occupy all of those other genes. This has got to be explained better. See my comment above (#2) on testing whether the R-loop resolution activity is even required for the effects on transcription. The identity of genes where R-loops are lost in RNaseH2-knockdown would be another interesting place to reanalyze and get additional insights.
-Later on Page 7 the authors hint at a very exciting model for why there are redundant pathways at long genes. Reading between the lines are you saying if a short gene forms an R-loop and gets 'stuck' the cell can afford to just make it over again, so degradation by RNaseH2 is preferred. For very long genes this is a bad strategy because degradation of that long transcript wastes a lot of energy and time to remake the long transcript, so other pathways predominate? I'd like the authors to confirm and expand on this model if they agree. Could analysis of DRIP peak changes in other siRNA conditions confirm that RNaseH2-effects short genes while other pathways affect long genes? -This paper (https://pubmed.ncbi.nlm.nih.gov/32747416/) generates DRIP data in a few other cell lines with other siRNAs, maybe the gene length effects could be analyzed in these data sets and compared with the gene length of DRIP-gain genes RNaseH2A? 7. I do not really think the model is explained well. How does R-loop degradation lead to efficient transcription? It would seem that it would degrade the transcript, how does this help efficiency? The authors may need to consider literature on stalled RNA polymerase and associated R-loops. Could the stabilized R-loops reflect a backlog of stalled polymerase that needs to be cleared for productive transcription?
Minor issues: -Page 4. The concluding sentence of the section "Taken together, our results imply that RNase H2 plays a role in gene transcription" is overstated. At this point in the story, the authors just finished show that RNaseH2 is recruited to the genome in a transcription dependent manner, it does not imply that RNaseH2 has a role in transcription.
-In figure 1A, siRNaseH2A shows complete KD. In figure 5C siRNaseH2A is not as good. I recognize that the cell lines are different but the differences are quite striking. Could this low penetrance of knockdown in Figure 5 have affected the phenotype? -Can you justify use of the fibroblast model versus a neuronal model system. A more relevant model system would strengthen the arguments. Indeed, the title of the paper really suggests a focus on AGS pathology, which is not well developed here.
-Information about what constitutes a gained DRIP peak or a lost DRIP peak should be included in the main text on Page 5. A reader will see that the total number of peaks does not add up with the gained/lost peaks. I assume this is due to a threshold of changes in peak reads but it would help to clarify exactly what the authors consider a gained/lost peak.
-The authors state in places that RNaseH2 forms a complex with RNA polymerase II. The only evidence shown is that they interact by co-IP and western. I think the word 'complex' may be overstating the results. We do not learn a lot in this study about when and how RNaseH2 interactions with RNA polymerase II occur.
-The rationale for using an alkaline comet assay in Figure 5 is unclear. Are the authors expecting double strand breaks? If not, then how could ssDNA breaks trigger an inflammatory response? A neutral comet assay might help them better connect the damage to STING activation.
-The legend for Figure 2C says ActD is compared to a DMSO vehicle but the figure says EtOH. This should be clarified.
-The legend for Figure 2 also refers to panel g, as (d).
-The legend for Figure 1 labels intronless JUNB as k, while it should be l.

Reviewer #3 (Remarks to the Author):
This is a nice paper showing a kind of unexpected role of RNASEH2 during transcription by RNA polII. Using DRIP-seq and ChIP-seq to analyze DNA-RNA hybrids and the presence RNA polII and RNASEH2A, the authors show an enrichment of RNASEH2A at the 5' end region of genes. Removal of RNASEH2 leads to an increase of hybrids mainly at the regions where RNASEH2A is enriched in normal cells that, as expected from previous studies, is associated with DNA damage. At least part of this damage is produced by structure-specific endonucleases, which is one mechanism of break formation. Consistent with the current literature, damage leads to an enhancement in the RNA levels of genes of the immune response. In general, the manuscript provides new and interesting results that make it a candidate for Nat Comm. I have few comments added below to improve the manuscript, but also some important requests. It seems that the manuscript provides ChIP-seq and DRIP-seq data performed only once. At least the DRIP-seq and ChIPseq of RNH2A should be performed minimally twice to show that results are repetitive, to make this a Nat Comm article. In addition the model proposed has to be better justified. It is pretty counterintuitive and the data are open to additional interpretations.

Specific comments
It would be good to justify why they chose for DRIP-qPCR of related genes RNU1 and RNU2 Rather than showing the metaplot of intron-plus versus intron-less genes, which really reflects a comparison of short versus long genes, it would be more informative to see the data of ChIP-seq of exons versus introns.
Authors cannot claim that RNASEH2 interacts with RNApolII as in page 5: "our results reveal that RNASEH2 is a part of the PolII complex which acts to promote transcription". For such an affirmation authors would need to show the purification by affinity chromatography and to identify the proteins by MALDI-TOFF, and not just by Westerns of co-IPs. The use of benzonase is not sufficient to conclude that RNAASEH2 associates with PolII in a stable manner regardless of DNA with the results provided. The data indicates that RNASEH2 associates with RNA polII, but not that it forms a complex with it.
The conclusion that RNASEH2 resolves co-transcriptional R loops needs to be further substantiated. Authors should produce a cell line expressing a catalytically-dead RNASEH2 to show that the nuclease activity is required for R loop resolution. This can be done by RT-qPCR in several of the genes detected to accumulate R loops in the DRIPseq. Alternatively, authors might consider the possibility of reducing R loops by overexpressing the three subunits of RNH2 together Authors should test whether RNASEH2 is recruited at regions accumulating R loops. Check at some of the RNH2 peaks whether this is reduced by RNASEH1 overexpression. This can be done in several regions by ChIP-qPCR. Wouldn't this be expected if RNASEH2 resolves those hybrids? I find the last point poorly connected with the rest of the ms. Certainly, the inflammatory response is a highly important phenomena that merits study, but authors should rationalize better how this relates with the rest of the paper. If the authors want to correlate the R loops with DNA damage as a way to strengthen conclusions is OK, but the rest seems to confirm that DNA damage will activate the inflammatory response. This needs to be discussed better. A main question is whether the action of RNASEH2 could be linked to a role in mitochondria or cytoplasm or other events. Can this be excluded? Fig. 4c with the plot of the DRIP-seq of snRNA data shows a peak downstream the TES. Authors need to discuss this result. Is this supposed to be a non-transcribed DNA region? What is the explanation for a hybrid signal higher than that observed inside the genes?  It is easy to double the RNA levels of a gene that is low expressed versus a gene that is highly expressed. This is important considering that results shown correspond to RT-qPCR values and not complete mRNAs. It is critical that the levels of expression of the genes used as controls are similar to those of the immunity response.
Authors should provide a main figure with a large region covering several genes, not just the length of one gene, so that we can compare the ChIP-seq, DRIP-seq, RNASEH2 pChIP-seq at once.  I would reconduct the discussion on intron-less and intron-containing genes. The data show that short genes have DRIP-seq signal covering a large part of the gene, whereas intron-containing genes the signal is concentrated on the 5' end. It seems that R loops are accumulated at the 5' end of genes therefore. In long genes, R loops are not seen at the middle and 3' end of genes. With the data observed, it is difficult to think that RNASEH2 travels with the transcription machinery resolving R loops, since almost no effect or presence of RNASEH2 is observed in the second half of genes longer than 2-kb. It seems its activity is limited only to the 5' end of genes. Intron-less genes and intron-containing genes <2kb shows similar profile indeed. This may be important to discuss in the model, since it may well be possible that RNASEH2 has a role aborting the elongation of suboptimal transcripts that form R loops; otherwise it would be counterproductive for the cell to degrade any long nascent RNA forming short hybrids. Otherwise, how can authors propose that an active RNH2 that would be removing nascent mRNAs forming short stretches of hybrids leads to efficient transcription. Unfortunately authors do not know directionality of the RNA forming the hybrids, since I am not sure whether RNASEH2 could remove hybrids formed with antisense RNA.
Authors should be homogeneous with the plots. Why for instance Ext Fig. 4c, e shows 0.5 kb and +1,5kb region upstream and downstream of genes, whereas g, I show -2 and +2,5 kb. Use in this and all other figures the same length of regions surrounding the genes, so that we can compare all data visually. The same criticism for fig. 1 and 3 metaplots. Indeed, it is not clear to me why the length upstream and downstream is not the same, making thus plots symmetrical.

Detailed Responses to the Reviewers' Comments
We thank the reviewers for their comments and are pleased that they all appreciate the novelty of our findings, in particular the role of RNase H2 function in transcription. In response to the reviewer's comments, we have introduced a number of requested changes, which allowed us to improve the quality and the clarity of our ms. In particular, we have expanded and strengthened the data in our manuscript as follows:  Fig. 3b). Fig. 4h, Supplem Fig. 6b and Fig. 5d). Altogether, these new results support a model where R-loops, accumulated due to RNase H2 deficiency especially on short genes, are processed by XPG/XPF endonucleases, which produce DNA breaks, contributing to increased inflammatory response characteristic of AGS pathology. Fig. R4

Reviewer #1
RNase H2, the subject of these studies, has two different functions. The most studied, at least in mammals, is the ribonucleotide excision repair (RER) activity, which initiates the removal of ribonucleotides incorporated in DNA during replication. This manuscript addresses the least known function of RNase H2 in processing the RNA strand of R-loops, which are structures formed after transcription when the RNA hybridizes back with the template strand. This work describes the association of RNase H2 to actively transcribed genes, analyzing RNase H2 binding to chromatin and its genomic distribution. An association to chromatin could be due to its RER activity, but they found the interaction to be independent of DNA replication by inhibiting DNA Pol and by using quiescent fibroblasts. They found that RNase H2 and RNA Pol II co-IP in the absence of nucleic acids, suggesting that they are part of the same complex. When RNase H2 is depleted, nascent transcripts are reduced for some gene categories but not (or very minimally) for intron-containing genes, which make the largest portion of RNA Pol II transcripts. Consistent with RNase H2 interacting and processing the R-loops of only a small subset of active genes, DRIP-seq showed more decreased/loss (35,604) than increased/gained (16,647) DRIP peaks in RNase H2 depleted cells, although selecting for genes that are strongly enriched for R-loops, there is an increase in R-loop signal upon RNase H2A depletion in most gene categories except in intron-containing genes. Finally, they try to establish a connection between R-loop accumulation in the absence of RNase H2 and DNA damage and the immune response found in AGS patients.
The main findings of the manuscript are: • RNase H2 interacts with RNA Pol II and acts co-transcriptionally removing R-loops presumably as they are formed to allow proper gene expression.
• There is a specific subset of genes that RNase H2 binds, leading to R-loop processing. This group of RNase H2-interacting genes are mostly short genes including histone, snRNA and intronless genes.
• They propose a mechanism for R-loop induced DNA damage and immune-response in RNase H2 defective and AGS mutants that requires structure-specific endonucleases cleaving the ssDNA portion of the R-loops. All these results are novel and would be of interest to the fields of RNase H studies, DNA damage and autoinflammatory disorders. Also, they would advance our understanding of how R-loop accumulation affects gene regulation. The data are well presented, and the statistical analyses are appropriate. However, before been accepted for publication a few issues should be addressed:

Response:
We would like to thank this reviewer for positive comments and highlighting the novelty of our manuscript and its suitability for publication in Nature Comm journal.
1. RNASEH2C mRNA is only depleted to about 60% by siRNASEH2C (Extended data figure  1C) and subsequently the protein level of RNase H2C is only reduced to about 50% ( Figure  1b) of wt levels forming RNase H2 complexes that are about 50% the amount in wt cells. These small decreases would presumably affect all subsequent data obtained using siRNASEH2C. I would suggest using siRNASH2B instead, which appears to be more effective.
Throughout this paper we have used all three siRNAs targeting H2A, H2B and H2C subunits independently, clearly demonstrating an increase in R-loop accumulation (Fig. 4e-f) and inflammation ( Fig.5b and Supplementary Fig.7b), irrespective of which RNase H2 subunit was depleted. These data support our overall conclusions. the fraction of chromatin bound RNase H2 subunits appears to be very similar after siLuc as after depletion of the different components of the RNase H2 complex. It seems that the depletion affects mostly the free form of RNase H2 but shows little effect on the chromatinbound form, or that the fraction of bound form is very small.
We provide the quantification of independent fractionation experiments (n=3-4) and more representative western blot in the new Supplementary Fig. 1e. Even though the efficiency of the RNase H2A depletion is lower in the chromatin fraction (~70%) compared to depletion of the free form of RNase H2A (~95%) (Fig 1b), we have observed a decrease of RNase H2A bound to the studied genes by ChIP-qPCR (Fig. 1h, j and l). This ensures that the reported DRIP changes for the analysed genes are likely to be direct effects of RNase H2 deficiency in the chromatin fraction.
3. Because RNase H2 would be expected to associate with chromatin as part of its RER function, it is important to show convincingly that the association of RNase H2 and RNA Pol II is strong in quiescent fibroblasts, which the data presented in Extended Data Figure  3b does not appear to support well. The inclusion of clear western blot data is needed to help substantiate this association.
We provide a new clearer WB in quiescent fibroblasts, supporting the association of RNase H2 with the total Pol II and transcription-proficient Pol II, phosphorylated at Ser2 and Ser5 residues of the CTD, independent of DNA replication (new Supplementary Fig 3b). 4. In figure 4b it is shown that RNase H2 peak coincides with the DRIP peak in cells with wt RNase H2, suggesting that RNase H2 binds but doesn't cleave R-loops enriched regions.
Could an explanation for this be proposed? Perhaps RNase H2 binds all or most R-loops but only processes a small portion of them.
Indeed, in Figure 4b we observe co-localization of DRIP and RNase H2 peaks, suggesting that RNase H2 is bound to many genes. R-loops occur co-transcriptionally and occupy ~5% of the human genome under physiological conditions (Sanz et al., 2016 . 4h and Supplementary Fig. 6b (Cerritelli et al., 2003). We have now added this information to the Materials and Methods section.
6. Does the RNase H1 overexpression system express only the nuclear form of the enzyme, or does it also express the mitochondrial form? This construct should be clearly described.
RNase H1 over-expression construct used in our experiments lacks mitochondrial localization signal (MLS) and hence is solely expressed in the nucleus (Cerritelli et al., 2003). We now provide this description in the Methods section.

Reviewer #2 (Remarks to the Author):
This manuscript describes the genome-wide profile of RNaseH2 binding to the human genome.
The main findings are that RNaseH2 associated with transcribed regions of the genome in a transcription-dependent manner and through physical association with RNA polymerase II. Loss of RNaseH2 function leads to defects in transcription that appear selective to specific types of transcripts, namely short intronless transcripts. As expected, loss of RNaseH2 leads to increases in R-loops at some loci. These R-loops can lead to DNA damage caused by the XPF/XPG nucleases and activate transcription of inflammatory response genes, which is relevant to the RNaseH2-deficiency disorder Aicardi-Goutieres syndrome. Overall, the manuscript is clear and straightforward and presents a novel finding that RNaseH2 regulates transcription through association with RNA polymerase II and transcribed genes.
I have a number of technical questions, and suggestions for additional analyses that could improve the work. In short, while Figures 1-3  A deeper exploration of some of these questions, even using the authors existing data and some assays they already have working would dramatically strengthen the manuscript.

Response:
We thank this reviewer for her/his positive comments and finding our manuscript 'clear and straightforward' and presenting 'a novel finding that RNaseH2 regulates transcription through association with RNA polymerase II and transcribed genes'. We want to highlight that the role of RNase H2 in co-transcriptional R-loop resolution (Figures 1-4) and the role of R-loops in inflammatory response in RNase H2-deficient cell ( Figure 5) in mammalian systems has not been reported so far and therefore both represent novel discoveries. Below we provide additional experiments and controls to support the role of RNase H2 in transcription, R-loop resolution and inflammatory response through DNA break production. These data are also incorporated in the manuscript to support our model and provide more clarity to our results.
Major issues: 1. The EU staining data seems to also show that nucleolar intensity is decreased. The authors should test whether RNaseH2 also affects RNA Polymerase I and III transcription, and whether RNA polymerase I and III can be observed in pulldowns of RNaseH2 (as in Fig. 3A). This is a missed opportunity to learn more about how RNaseH2 is actually recruited. For example, if all three polymerases could recruit RNaseH2 then it would suggest that a shared subunit may be responsible for the interaction.
We have now provided the quantification of total, nucleoplasmic and nucleolar EU signal by using an automated analysis with high-content microscopy in both HeLa and HEK293T cells (>20,000 cells analysed per condition) (new Fig. 3c and Supplementary Fig. 3d-e) Fig. 3c).  (Response Fig R5a). These cells demonstrated an increase in micronuclei accumulation, as previously reported, and an increase in R-loops on specific genomic loci by DRIP-qPCR, in line with our data in RNase H2A-deficient HeLa cells (Response Fig R5b-c).
Over-expression of a plasmid encoding all three RNase H2 subunits provided by A.Jackson's lab, caused a reduction of elevated R-loops in RNASEH2A KO cells, supporting a role of RNase H2 in R-loop resolution (Response Fig R5) Figure 5f seem to normalize both the siLuc and siXPG to 1 for the mRNA levels. I think the siXPG should not be normalized and should be compared directly to siLuc. Does XPG or XPF knockdown alone increase inflammatory gene expression? It may be that the relative increase in siRNAseH2A is lower, but if the background in siXPG is much higher it could change the interpretation. The way the data is presented does not allow for this kind of comparison.

The induction of immune related genes by qPCR
We now present a figure where all data points are directly compared to siLuc (new Supplementary Fig. 8d and 8g)

and siLuc cells to examine the contribution of these endonucleases to the immunity in RNase H2-deficient cells beyond their roles in other pathways (i.e. by comparing XPGproficient (siLuc cells) and XPG-deficient (siXPG cells) cells upon depletion of RNase H2A).
4. In Figure 5e, Might the authors have expected that XPF depletion on its own would have caused DNA damage. The box plot should perhaps show the individual data points, it seems like the siXPF sample has a long tail of cells with damage. Is the distribution normal? Can the authors do a statistical test of siXPF versus control to see if there is an increase in comet tail moment? Currently the siXPF bar (purple) is not compared to the control siRNA bar (white) as far as I can see. This should be done and discussed. Which post-hoc statistical test was used should be indicated in the legend also. In addition, if the damage is really due to R-loops RNaseH1 expression could be included as an additional control, especially since XPF/XPG knockdown do not completely suppress the damage. Fig  8c). We . 5d). These results further support a contribution of R-loops to accumulation of DNA breaks in RNase H2deficient cells.

As described in the response to point 3, XPF is involved in DNA damage repair and its depletion may result in DNA damage as reported by both γH2AX and phopsho 53BP1 foci staining in non-replicating fibroblasts (Cristini et al. 2019; Fig S7C) and COMET assay in U2OS cells (Li et al. 2019; Fig.6C). We have now enlarged our alkaline COMET analysis in Fig 5e to include more cells (n>400) and provide individual data points (Supplementary
Response Fig. R1

5.
Is it possible that the immune genes are directly affected by RNaseH2A knockdown due to the transcriptional role? To address any effects the authors could analyze the DRIP, RNAPolII and RNaseH2A occupancy at all of the reporter genes (TNF, STING etc). This is important to rule out direct effects on transcription as opposed to DNA damage-cytoplasmic DNA induced activation. Similarly, the authors rely on mRNA expression but looking at protein level induction and possibly at micronuclei as a cause of STING activation would fill out the story. Additional data to help us understand how these R-loops trigger an inflammatory response would help better justify the focus on AGS in the title.
Below we now provide the RNase H2A/DRIP/chrRNA occupancy screen shots (Response Fig.  R2). chrRNA-seq analysis of these genes shows their increased transcription. However, RNase H2 is not bound to these genes based on lack of RNase H2 IP enrichment over input in ChIPseq lanes and therefore ruling out a direct effect of RNase H2 KD on transcription of immunity genes. Moreover, most of these genes are expressed at a low level, resulting in a very low DRIP signal which is close to the RNase H-digested background control DRIP sample. Supplementary Fig 7c), which are in agreement with previous literature (Pizzi et al;2015). Finally, we demonstrate that R-loops contribute to DNA breaks in RNase H2A-depleted cells by alkaline comet assay with RNase H1 overexpression (new Fig  5d). Taken together, these data suggest that persistent R-loops in cells deficient for RNase H2 promote DNA break formation which contributes to the inflammatory response.

We also provide new experiments showing a significant increase of micronuclei in RNase H2Adepleted HeLa cells (new
Response Fig. R2: Overlay between ChrRNA-seq, RNase H2A ChIP-seq and DRIP-seq profiles for IFNGR1, PTGS2, OAS1, and ISG20 genes in HeLa cells. For ChrRNA-seq and DRIP-Seq HeLa cells transfected with siLuc or siRNASEH2A were used. 6. The bias toward short genes is not really explained because RNaseH2 and DRIP signal still occupy a lot of normal genes. If it is only when RNaseH2 is depleted that the effect on short genes is seen, then why does it RNaseH2 occupy all of those other genes. This has got to be explained better. See my comment above (#2) on testing whether the R-loop resolution activity is even required for the effects on transcription. The identity of genes where R-loops are lost in RNaseH2-knockdown would be another interesting place to reanalyze and get additional insights.
As requested, we have performed a Gene Ontology analysis of genes where R-loops are lost or gained in RNase H2-deficient cells. However, we have found no stand-out groupings (no group with a fold change >1.5) that might help rationalize why some genes are affected whereas others are not (Response Fig. R3 above).

Response Fig. R4: Meta-analysis of DRIP-seq on short (<2 kb) and long (>10 kb) intron-containing genes in U2OS cells depleted for DDX5 (a), PRMT5 (b) and XRN2 (c).
The same genes analyzed in siRNASEH2A experiments ( Supplementary Fig. 5) Fig. R4a-d). We now provide further discussion of this point in the revised manuscript (ms page 8), indicating that RNase H2 acts preferentially on short genes whereas TOP1 (Manzo et al., 2018) (Groh et al, 2014). We now further discuss these points in the discussion section of the revised paper (ms page 8).

Minor issues:
-Page 4. The concluding sentence of the section "Taken together, our results imply that RNase H2 plays a role in gene transcription" is overstated. At this point in the story, the authors just finished show that RNaseH2 is recruited to the genome in a transcription dependent manner, it does not imply that RNaseH2 has a role in transcription.
Thank you for pointing this out. To better reflect our experimental results, we have toned down the text to state that 'our results suggest that RNase H2 may play a role in gene transcription'.
-In figure 1A, siRNaseH2A shows complete KD. In figure 5C siRNaseH2A is not as good. I recognize that the cell lines are different but the differences are quite striking. Could this low penetrance of knockdown in Figure 5 have affected the phenotype?
We observe that the efficiency of the RNase H2A RNAi-mediated knock-down is similar on mRNA levels in HEK293T and HeLa cells (e.g. compare Supplementary Fig 1c and 6a). However, on a protein level, it is lower in HEK293T (Fig.5c corresponding to new Fig. 4g; Supplementary Fig. 3d) compared to HeLa cells (Fig.1a-b; Supplementary Fig.1c-e). This may reflect the differential stability of the RNaseH2 complex in these two cellular models. However, despite these differences, transcriptional defects, R-loops, DNA damage and increased expression of inflammatory genes were consistently observed upon siRNaseH2A in both HeLa and HEK293T cell lines (e.g. compare Fig 5b and 5c; Fig.5d and 5e), further supporting our conclusions. Generally, we observed that a more efficient RNase H2A depletion leads to a stronger phenotype.
-Can you justify use of the fibroblast model versus a neuronal model system. A more relevant model system would strengthen. the arguments. Indeed, the title of the paper really suggests a focus on AGS pathology, which is not well developed here -Information about what constitutes a gained DRIP peak or a lost DRIP peak should be included in the main text on Page 5. A reader will see that the total number of peaks does not add up with the gained/lost peaks. I assume this is due to a threshold of changes in peak reads but it would help to clarify exactly what the authors consider a gained/lost peak.

We used fibroblasts here as a model for non-replicative cells (and not AGS model) as it has been extensively used in
The detailed description of peak quantification and assignment to the 'gain'/'loss' categories is now provided in the Supplementary Methods 'ChIP/DRIP-seq data processing' section of the paper. In brief, total number of peaks for siLuc and siRNaseH2A samples were obtained by comparing each IP to its respective input, and normalized to IP+RNase H control to avoid unequal non-R-loop background level in DRIP-seq. The peaks were assigned into 'gain/loss' categories based on the ratio of the reads in siRNASEH2A vs siLuc samples (<0.5: decreased/lost; >2: increased/gain; others: unchanged). The higher number of gained/lost peaks compared to the total number of DRIP peaks for siLuc and siRNASEH2A is due to the difference in the peak calling algorithm used (MACS2 callpeak vs MACS2 bdgdiff) and the breakdown of the initial peaks into smaller peaks when one or more parts of an initial peak are enriched differently in siLuc or siRNASEH2A samples. We feel that Methods section now provides sufficient information about peaks assignment. However if required, we can also provide it in the main text of the paper.
-The authors state in places that RNaseH2 forms a complex with RNA polymerase II. The only evidence shown is that they interact by co-IP and western. I think the word 'complex' may be overstating the results. We do not learn a lot in this study about when and how RNaseH2 interactions with RNA polymerase II occur.
We fully agree with this comment and therefore we have now toned down the text to state that 'RNase H2 associates with the Pol II complex' in the text. Since this paper is primarily focusing on the role of RNase H2 in R-loop resolution, we feel that the specifics of RNase H2 and Pol II interaction are beyond the scope of this paper and require a separate investigation.
-The rationale for using an alkaline comet assay in Figure 5 is unclear. Are the authors expecting double strand breaks? If not, then how could ssDNA breaks trigger an inflammatory response? A neutral comet assay might help them better connect the damage to STING activation.
To assess the overall level of DNA damage, alkaline COMET assay was used in Fig.5, which detects both SSBs and DSBs. Both ssDNA and/or RNA/DNA hybrids released from R-loops by combined ssDNA cleavage events mediated by XPG/XPF (as reported in Cristini et al. 2019) could also elicit an inflammatory response (Shen et al, 2015;Coquel et al., 2018). Following the reviewer's suggestion, we have also carried out Neutral comet assay (new Supplementary  Fig. 8a). We observed an increase in DSBs in RNase H2-depleted cells, which is in line with previous studies. This suggests that DNA damage drives STING activation in AGS conditions.
-The legend for Figure 2C says ActD is compared to a DMSO vehicle but the figure says EtOH. This should be clarified.
We have changed the legend accordingly.
-The legend for Figure 2 also refers to panel g, as (d).
We have changed the legend accordingly.
-The legend for Figure 1 labels intronless JUNB as k, while it should be l.

We have changed the legend accordingly.
This is a nice paper showing a kind of unexpected role of RNASEH2 during transcription by RNA polII. Using DRIP-seq and ChIP-seq to analyze DNA-RNA hybrids and the presence RNA polII and RNASEH2A, the authors show an enrichment of RNASEH2A at the 5' end region of genes. Removal of RNASEH2 leads to an increase of hybrids mainly at the regions where RNASEH2A is enriched in normal cells that, as expected from previous studies, is associated with DNA damage. At least part of this damage is produced by structure-specific endonucleases, which is one mechanism of break formation. Consistent with the current literature, damage leads to an enhancement in the RNA levels of genes of the immune response.
In general, the manuscript provides new and interesting results that make it a candidate for Nat Comm. I have few comments added below to improve the manuscript, but also some important requests. It seems that the manuscript provides ChIP-seq and DRIP-seq data performed only once.  FigR5a-b). In these KO cells we have observed an increase in R-loops on specific genomic loci by DRIP-qPCR (Response Fig R5c), in line with our data in RNase H2A-deficient HeLa cells (Figure 4f).  Fig 6c- 6. I find the last point poorly connected with the rest of the ms. Certainly, the inflammatory response is a highly important phenomena that merits study, but authors should rationalize better how this relates with the rest of the paper. If the authors want to correlate the R loops with DNA damage as a way to strengthen conclusions is OK, but the rest seems to confirm that DNA damage will activate the inflammatory response. This needs to be discussed better. A main question is whether the action of RNASEH2 could be linked to a role in mitochondria or cytoplasm or other events. Can this be excluded? 7. Fig. 4c with the plot of the DRIP-seq of snRNA data shows a peak downstream the TES. Authors need to discuss this result. Is this supposed to be a non-transcribed DNA region? What is the explanation for a hybrid signal higher than that observed inside the genes?  Stathaki et al 2011). Therefore, we predict that these R-loops at the 3' end of snRNA genes may be also involved in transcriptional termination. 8. Fig. 4f. Experiments should show that RNH1 removes the DRIP-qPCR signals in the genes tested.
We have now demonstrated that over-expression of RNase H1 in HEK293T cells results in a decrease of R-loop levels elevated by RNase H2 depletion, further supporting the role of RNase H2 in co-transcriptional R-loop resolution (new Fig.4h and Supplementary  Fig.6b). 9. Fig. 5. Authors need to show the absolute values of mRNA levels, so that the reader can compare different genes. It is easy to double the RNA levels of a gene that is low expressed versus a gene that is highly expressed. This is important considering that results shown correspond to RT-qPCR values and not complete mRNAs. It is critical that the levels of expression of the genes used as controls are similar to those of the immunity response.
The mRNA results presented in Fig 5 are 10. Authors should provide a main figure with a large region covering several genes, not just the length of one gene, so that we can compare the ChIP-seq, DRIP-seq, RNASEH2 pChIP-seq at once. Supplementary Fig 4b-c. 11. Fig. 5 Considering that results shown correspond to RT-qPCR values, it would be relevant to show a scheme showing which regions has been RT-qPCR to make conclusions. Supplementary  Fig. 7a. 12. Fig. 5e. Authors need to show that RNH1 suppresses the comet result, otherwise the result can be explained by the DNA-inserted ribonucleotide removal activity of RNASEH2

We now have included a scheme showing positions of RT-qPCR primers in
As requested, we have carried out alkaline comet assay in HEK293T cells over-expressing RNase H1 (new Fig. 5d). These new results show that RNase H1 decreases DNA breaks accumulating in the absence of RNase H2. This indicates that the DNA damage induced by the depletion of RNase H2 is at least partially R-loop-dependent. 13. I would reconduct the discussion on intron-less and intron-containing genes. The data show that short genes have DRIP-seq signal covering a large part of the gene, whereas intron-containing genes the signal is concentrated on the 5' end. It seems that R loops are accumulated at the 5' end of genes therefore. In long genes, R loops are not seen at the middle and 3' end of genes. With the data observed, it is difficult to think that RNASEH2 travels with the transcription machinery resolving R loops, since almost no effect or presence of RNASEH2 is observed in the second half of genes longer than 2-kb. It seems its activity is limited only to the 5' end of genes. Intron-less genes and intron-containing genes <2kb shows similar profile indeed. This may be important to discuss in the model, since it may well be possible that RNASEH2 has a role aborting the elongation of suboptimal transcripts that form R loops; otherwise it would be counterproductive for the cell to degrade any long nascent RNA forming short hybrids. Otherwise, how can authors propose that an active RNH2 that would be removing nascent mRNAs forming short stretches of hybrids leads to efficient transcription. Unfortunately authors do not know Response Fig. R7: Comparison of mRNA levels between immunityrelated and control genes. RT-qPCR ΔΔCt analysis of mRNA levels for all immunity-related genes and two control genes (TUBG2 and SELENBP1, indicated as SBP). For comparison, PTGS2 mRNA in siLuc condition is set to 1. directionality of the RNA forming the hybrids, since I am not sure whether RNASEH2 could remove hybrids formed with antisense RNA.
The DRIP-seq results confirm that the long genes have R-loops enriched over input within the body of the genes, however this signal is dramatically enriched over the 5'end of the gene (Supplementary Fig. 5f). In contrast, the level of R-loops is consistently high over the whole body of the short genes (Supplementary Fig. 5b and d). DRIP (Fig 2a). Therefore, we predict that RNase H2 function is more likely to be associated with the sense transcription and therefore sense hybrid removal.
14. Authors should be homogeneous with the plots. Why for instance Ext Fig. 4c, e shows 0.5 kb and +1,5kb region upstream and downstream of genes, whereas g, I show -2 and +2,5 kb. Use in this and all other figures the same length of regions surrounding the genes, so that we can compare all data visually. The same criticism for fig. 1 and 3